The purpose of our work has been to develop a mathematical basis for the use of light in medical diagnosis and therapy. Recent studies have focused on assessing the optical contrast arising from abnormally absorbing regions in tissue. Random walk theory has been used to derive a time-dependent contrast function which can be used in transillumination, time-resolved detection. Computer codes have been written which are the basis of a rudimentary universal scheme for assessing target size and location. The theory and related computer algorithms have been tested with data provided by experimental collaborators at University College, London. Related work has been undertaken to develop schemes for detection of fluorescent-labeled targets lying within optically turbid tissue. A collaborative project is underway, involving personnel in NIDR and FDA, to develop a non-invasive, i situ fluorescent detector-scheme for Sjogren's syndrome, which is an auto immune exocrinopathy, involving salivary glands which are invaded by activated mononuclear cells. Other studies relate to optical properties of deep lying tissue, for example to determine the oxygenation state of hemoglobin in the brain. Included among recent projects is a mathematical investigation of resolution limits for time-resolved imaging of human breast. In this project we derived an analytical theory to calculate the line spread function of time-resolved photons as they cross different plane inside a finite slab. Experimental confirmation of this theory has been obtained from experiments done with collaborators at University College, London. Another recent project is directed towards the development of an analytical theory to assess the contrast obtainable in a transillumination measurement. This study accounts for the face that the absorbance of a tissue inclusion may not be very different from that of normal tissue. We have derived a theory that presently pertains to relatively small localized targets. This work currently is being extended to targets of arbitrary siz and shape. The ultimate goal is to develop an iterative scheme for inverting transmission data to reconstruct images from actual tissue.